In the current environment, traffic is getting increasingly congested as the number of vehicles increases year by year. Especially in the case of large flows of motor vehicles and pedestrians during rush hour, it is particularly important to solve the conflict between motor vehicles and pedestrians, and to ensure the smooth passage of both motor vehicles and pedestrians. As information technology, communication technology, sensor technology, control technology, computer technology, etc., are effectively applied to the entire traffic management system, a more efficient intelligent traffic system for integrated traffic management has been gradually set up.
At present, some traffic optimization schemes have been provided for the intelligent traffic system. One traffic optimization scheme is to simulate traffic flows at intersections of signaling control based on a cellular automaton. The scheme models and simulates dynamic traffic flows at intersections of signaling control using a cellular automaton method, which can implement a complicated traffic condition through simple computation and optimize timing of signals by comparing a simulation result with an original input scheme. Although the traffic condition is simplified, the scheme does not specifically solve the conflict between pedestrians and motor vehicles.
Another traffic optimization scheme is signal timing optimization at single-point intersections under mixed traffic conditions. The scheme is based on running characteristics and compositions of mixed traffic flows of urban road traffic. The influences of the mixed traffic flows on the signal control scheme are generalized into unreasonable allocation of right of way between motor vehicles and slow traffic at intersections and interference of pedestrian crossing signals to motor vehicle flows at road sections. Although the mutual influence between pedestrians and motor vehicles is taken into account, the scheme mainly focuses on the motor vehicles and does not fully consider the passage of the pedestrians.
The existing technical solutions mainly rely on GPS, geomagnetic induction, etc., to obtain traffic flow data from motor vehicles, but do not provide an effective way to comprehensively obtain traffic condition information of pedestrians and non-motor vehicles, leading to obvious data deviations. As a result, these schemes cannot effectively and comprehensively take into account various traffic subjects such as motor vehicles, pedestrians and non-motor vehicles, and are difficult to obtain an optimal control effect.